|Teaching method||Contact hours|
|Course coordinator(s)||dr LW Kiewidt|
|Lecturer(s)||dr LW Kiewidt|
|Examiner(s)||dr LW Kiewidt|
Language of instruction:
Assumed knowledge on:
BPE-10305 Process Engineering Basics or equivalent
BCT-30806 Physical Modelling; MAT-26306 Control Engineering; BCT-31306 Systems and Control Theory; MAT-31806 Parameter Estimation and Model Structure Identification.
In this course you will learn how to describe and how to model the time behaviour of various systems and processes. The modelling starts with the development of mathematical models based on mass and energy balances, mechanics or the kinetics of chemical and biological reactions. The approach is generic and can be applied to all kind of systems, such as the growth of plants and microorganisms, biological and chemical reactions in bioreactors, greenhouses, food processing, and to biological systems. These models are important for answering research questions about the time behaviour of these processes and for (re)designing a system.
The course starts with the translation of oral and written problems into a mathematical model by organizing the information in sketch, diagram or drawing. Next the non-steady state balances for this system are formulated using scientific knowledge and measurement data. Furthermore you will learn how to solve the mathematical model and to analyse the dynamic behaviour of the modelled system. Several techniques, methods and model representations will be used to represent and analyse the dynamic systems. Once a model is formulated for a system, the model needs to be verified with experimental data. Techniques and limitations of methods to fit the models to data are discussed and exercised.
The methods learned in the course will be demonstrated by discussing several application examples in the lectures and by a practical for simulation and analysis.
After successful completion of this course students are expected to be able to:
- create a mathematical systems model from an oral or written problem description of a simple system through application of scientific knowledge and measurement data;
- translate mathematical systems models into differential equation models and to solve and analyse these models;
- write the differential equations in state-space form;
- understand and recognize the different types of variables of a systems model written in state-space form;
- approximate non-linear systems by linearized systems;
- determine and compute system behaviour, equilibriums, and system properties such as stability;
- represent elementary linear systems by means of a state-space model and convert one into the other;
- apply parameter estimation to estimate unknown parameters of a mathematical systems model in state-space form.
- computer exercises;
- independent study.
Closed book exam consisting of closed and open questions (grade at least 5.5). Observations during practicals. Oral examination at the end of each practical (pass/fail). All practical exercises have to be passed.
A course reader will be available in digital form.
|Compulsory for:||BAT||Biosystems Engineering||BSc||2MO|
|Restricted Optional for:||BBT||Biotechnology||BSc||2MO|
|MBT||Biotechnology||MSc||D: Process Technology||2MO|
|MBT||Biotechnology||MSc||E: Environmental and Biobased Biotechnology||2MO|
|MFT||Food Technology||MSc||H: Sustainable Food Process Engineering||2MO|